15013 results for "cancer studies using rna-seq"

in 13.56 milliseconds.

• Spatial RNA-sequencing of metastatic melanoma

  We performed RNA sequencing of 48 different regions sub-sampled from a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor. RNAseq was performed on samples with a minimum RNA integrity number (RIN) of 5.5 except for two cases (6A10 and 8A3) with RINs greater than 3. A minimum of 700ng of RNA were required for all samples undergoing RNAseq. Paired-end transcriptome reads were aligned using TopHat2, to the UCSC hg19 reference genome.

  Dataset EGAD00001005820

• Comprehensive assay for the molecular profiling of cancer by target enrichment from formalin-fixed paraffin-embedded specimens

  Tumor molecular profiling is becoming a standard of care for patients with cancer, but the optimal platform for cancer sequencing remains undetermined. We established a comprehensive assay, the Todai OncoPanel (TOP), which consists of DNA and RNA hybridization capture-based next-generation sequencing panels. A novel method for target enrichment, named the junction capture method, was developed for the RNA panel to accurately and cost-effectively detect 365 fusion genes as well as aberrantly spliced transcripts. The TOP RNA panel can also measure the expression profiles of an additional 109 genes. The TOP DNA panel was developed to detect single nucleotide variants and insertions/deletions for 464 genes, to calculate tumor mutation burden and microsatellite instability status, and to infer chromosomal copy number. Clinically relevant somatic mutations were identified in 32.2% (59/183) of patients by prospective TOP testing, signifying the clinical utility of TOP for providing personalized medicine to cancer patients.

  Study JGAS000164

• NextGen Consortium: GENESiPS Study: Identifying the Gene Networks of Insulin Resistance

  Variability in induced pluripotent stem cell (iPSC) lines remains a roadblock for disease modeling and regenerative medicine. Through linear mixed models we have described different sources of gene expression variability from RNA sequencing data in 317 human iPSC lines from 101 individuals. We found that ~50% of genome-wide expression variability is explained by variation across individuals and identified a set of expression quantitative trait loci that contribute to this variation. These analyses coupled with allele specific expression show that iPSCs retain a subject-specific gene expression pattern. Pathway enrichment and key driver analyses, based on predictive causal gene networks, found that Polycomb targets explain a significant part of the non-genetic variability present in iPSCs within and across individuals. These publically available iPSC lines and genetic datasets will be a resource to the scientific community and will open new avenues to reduce variability in iPSCs and improve their utility in disease modeling. SNP array data from individuals included in RNA-seq transcriptome profiling study of human induced pluripotent stem cells to characterize gene expression variation across individuals and within multiple iPSC lines from the same individual. Genotyping was performed on patient blood. Data availability: SNP-genotyping: dbGaP - current study RNA-seq counts: GEO - GSE79636 FASTQ files: SRA - SRP072417

  Study phs001139

• Single-cell/single-nucleus RNA-seq of Embryonal Tumor with Multilayered Rosettes (ETMR)

  Embryonal tumor with multilayered rosettes (ETMR) is a pediatric brain tumor with dismal prognosis. We analyzed eleven ETMR patient samples using single-cell transcriptomics. We reveal a spatially distinct cellular hierarchy that spans highly proliferative neural stem-like cells and more differentiated neuron-like cells. C19MC is predominantly expressed in stem-like cells and controls a transcriptional network governing stemness and lineage commitment. Systematic analysis of receptor-ligand interactions between malignant cell types reveals FGFR and NOTCH signaling as oncogenic pathways. Our study provides fundamental insights into ETMR pathobiology and a powerful rationale for more effective targeted therapies.

  Study EGAS50000000937

• Whole Exome and RNA-Sequencing of Germline, Small Bowel Carcinoid Primary Tumor, and Liver Metastasis Trios

  This dataset includes trios of germline/constitutional, primary tumor (small bowel carcinoid), and metastatic tumor (liver) trios for 5 patients (i.e. 15 samples total). Constitutional, primary tumor, and metastatic tumor samples all underwent whole exome sequencing (WES or WXS). Primary and metastatic tumor samples underwent RNA sequencing (RNA-seq).

  Dataset EGAD00001010036

• Integrated RNA-seq analysis of tumor thrombus

  We prospectively enrolled 83 patients with a renal mass and TT scheduled to undergo surgical resection. To accurately integrate genomic and transcriptomic findings and enable histological co-registration, simultaneous isolation of DNA and RNA was performed from individual samples characterized histologically through immediately flanking sections

  Study EGAS00001005512

• “Castration-persistence” is a distinct state of tolerance to androgen receptor targeting therapies in prostate cancer

  Androgen receptor (AR) signalling is important in prostate cancer progression, and therapies that specifically target this pathway are the mainstay of treatment for advanced disease. Treatment however is non-curative, and resistance develops inevitably with time. Although the mechanisms that drive progressive ‘castration resistant’ disease are reasonably well characterized, how tumours survive acute pathway inhibition is unclear. We performed a neo-adjuvant study of a novel combination of AR targeting therapies, and noted that the objective response to treatment was highly variable. To determine what was driving tumour persistence in poorly responding patients, we comprehensively characterised pre- and post-treatment samples were using both whole genome and RNA-sequencing. We find that ‘castration-persistence’ is a distinct state from ‘castration-resistance’, and is mediated by global transcriptional reprogramming leading to transitional EMT state, which is shared with benign luminal epithelial cells. This appears to be AP-1 and KLF driven, and represents and integration of multiple signalling pathways, particularly IGF2, offering a number of tractable strategies to improve clinical response to AR targeting therapies.

  Study EGAS00001003172

• Supraphysiologic MDM2 Expression Impacts P53-Independent Chromatin Networks and Therapeutic Responses in Sarcoma

  We collected multiple liposarcoma samples from different patients, including different subtypes (DD, WD) and normal adipose tissue as control. This study provides the biggest liposarcoma cohort to date, and examined the molecular regulatory circuits associated with MDM2 overexpression. To this end, we obtained not only RNA-seq data, but also ChIP-seq from Jun, RUNX, MDM2, P53 and H3K27ac, as well as hiChIP from tumor samples and cell lines. We found that MDM2 binds to thousands of genes involved in cellular growth and stress response in a P53-independent manner. Furthermore, we described these active genes engaged in multi-way topological interactions that resemble transcriptional hubs.

  Study phs003272

• Genome-wide chromatin accessibility profiling of primary human glomerular and kidney cortex tubular outgrowth cultures

  We generated primary cultures from mechanically isolated kidney glomeruli (filtration unit of the nephron) which are composed of podocytes and mesangial cells. In parallel, we generated primary kidney cortex tubule cell cultures, which are composed primarily of proximal tubule cells. Early passage cultures of these two cell types were subjected to chromatin accessibility profiling (DNase-Seq) and gene expression profiling (RNA-Seq). We found thousands of dynamically regulated enhancers in both cell types that potentially regulate nearby and distal target genes that are differentially expressed. These data will be useful for understanding the epigenomic regulation of gene transcription in key kidney cell types.

  Study phs001720

• Transcriptome of CD4+ T cells and CD8+ T cells in glioblastoma multiforme

  Patients included in this study were over 18 years of age and had a histology-confirmed diagnosis of glioblastoma multiforme (GBM). Exclusion criteria were the previous administration of any anti-tumor therapy including radiation therapy. All patients gave written informed consent. The study was approved by the local ethics committee (TUM Medical school) and conducted following the Declaration of Helsinki. During resection of the tumors, tumor tissue and tissue from normal appearing brain within the operative channel was collected. Blood was drawn during the surgical procedure. Single cell suspensions were prepared from the tumor tissue, the normal appearing brain, and the blood. CD4+ T cells and CD8+ T cells were sorted by flow cytometry. Only patients with a complete set of specimens (CD4+ tumor infiltrating lymphocytes (TIL), CD8+ TIL, CD4+ T cells from normal appearing brain, CD8+ T cells from normal appearing brain, blood-derived CD4+ and CD8+ T cells) containing a minimum of 1000 cells in each sorted sample were further analyzed (n=9). Total RNA was isolated from sorted cell populations using the RNAeasy Plus micro kit (Qiagen, 74034). Quality and integrity of total RNA was controlled on a Bioanalyzer 2100 (Agilent Technologies). Library preparation for bulk-sequencing of poly(A)-RNA was done as described previously (Parekh et al., 2016). Briefly, barcoded cDNA of each sample was generated with a Maxima RT polymerase (ThermoFisher Scientific, EP0742) using oligo-dT primer containing barcodes, unique molecular identifiers (UMIs) and an adaptor. Ends of the cDNAs were extended by a template switch oligo (TSO) and full-length cDNA was amplified with primers binding to the TSO-site and the adaptor. NEB UltraII FS kit was used to fragment cDNA. After end repair and A-tailing, a TruSeq adapter was ligated and 3'-end-fragments were finally amplified using primers with Illumina P5 and P7 overhangs. In comparison to previous descriptions (Parekh et al., 2016), the P5 and P7 sites were exchanged to allow sequencing of the cDNA in read 1 and barcodes and UMIs in read 2 to achieve a better cluster recognition. The library was sequenced on a NextSeq 500 (Illumina) with 59 cycles for the cDNA in read 1 and 16 cycles for the barcodes and UMIs in read 2. Data were processed using the published Drop-seq pipeline (v1.0) to generate sample- and gene-wise UMI tables (Macosko et al., 2015). Reference genome (GRCh38) was used for alignment. Transcript and gene definitions were used according to the Genecode Annotation Version 35.

  Dataset EGAD50000000226